MATLAB psoptimset

PSOPTIMSET is a MATLAB function that creates an options structure for the Particle Swarm Optimization (PSO) algorithm. The options structure is used to set various parameters for the PSO algorithm such as the maximum number of iterations, the population size, the tolerance for stopping criteria, and the display of output information during the optimization process.

The syntax for using PSOPTIMSET is:

options = psoptimset('parameter1', value1, 'parameter2', value2, ...)

where 'parameter' is the name of the PSO option and 'value' is the value assigned to that option. Some of the commonly used options are:

- 'Display': This option determines the level of output displayed during the optimization process. The possible values are 'off', 'iter', and 'final'. 'off' means no output is displayed, 'iter' displays output at each iteration, and 'final' displays output only at the end of the optimization process.

- 'MaxIter': This option sets the maximum number of iterations for the PSO algorithm.

- 'TolFun': This option sets the tolerance for the objective function. The optimization process will stop when the relative change in the objective function value is less than the value set for this option.

- 'PopulationSize': This option sets the size of the population for the PSO algorithm.

- 'PlotFcns': This option sets the plot functions to be used during the optimization process.

After creating the options structure using PSOPTIMSET, it can be passed as an input argument to the PSO algorithm using the PSO function. For example:

options = psoptimset('Display','iter','MaxIter',100);
[x,fval] = pso(@myfun,nvars,[],[],[],[],lb,ub,[],options);

In this example, the PSO algorithm is run with options that display output at each iteration and set the maximum number of iterations to 100. The PSO algorithm is solving the optimization problem defined by the function 'myfun' with nvars variables, no linear constraints, and bounds specified by lb and ub. The output of the optimization process is the solution x and the objective function value fval.